The subject matter generally relates to the field of radiology imaging and, more particularly, to a system and method to create a visualization that enables faster analysis of radiology image data. Although the subject matter is described with respect to medical imaging, and in particular mammography, the subject matter can also be applied to industrial imaging of miscellaneous subject matter (e.g., security screening, etc.).
Radiology imaging generally employs translation of a measured attenuation of transmitted x-rays through an imaged subject into image data of the anatomical structure of the imaged subject for illustration on a display.
A certain known type of radiological imaging system is employed in mammography to acquire radiological images of breast tissue. Generally, multiple different views of the breast tissue are desired in diagnostic mammography. Each of the multiple different views generally corresponds to a different position of the X-ray source and the image receiver in relation to the breast tissue.
Mammography is widely used today in the detection of radiological signs associated with lesions and the prevention of breast cancer. These signs may be either calcium deposits or cases of opacity. Calcium deposits are called microcalcifications and individually form small-sized elements (ranging from 100 μm to 1 mm in diameter) that are more opaque to X-rays than the surrounding tissues. Opacities are dense regions where the X-rays are absorbed more intensely than in the adjacent regions.
A typical mammography image generally includes projections of superimposed structures that interfere with a desired visibility of the breast tissue. These projections of the superimposed structures increase opportunities of a false positive interpretation if a structure resembles a lesion, or a false negative interpretation if the structure obscures the visibility of the lesion.
A typical resolution of a mammography image detector is about 100 μm. To address the limitations of projected views in mammography images, image data is acquired from several projections and at different angles of a volume of interest. This image data is then applied to a tomography reconstruction algorithm to create a digital, three-dimensional reconstruction of the volume of interest. As a result of the above, screening or interpretation of this digital, three-dimensional reconstruction of the volume of interest typically involves screening or reviewing of a large amount of image data in a sequential manner on a slice-by-slice (e.g., 50 to 80 tomography slices of image data) in the search for a small piece of information of clinical interest, such as a radiological sign of between 100 μm and 1 mm in size.